Biofuel Cells for Self‐Powered Electrochemical Biosensing and Logic Biosensing: A Review

This article reviews recent advances and progress in developing electrochemical (EC) biosensing and logic biosensing systems based on self‐powered biofuel cells (BFCs). BFCs that exploit enzymes and microbes have attracted a considerable recent interest owing to their unique ability to provide sustainable energy from renewable fuel source under mild conditions. This review focuses on recently introduced novel concepts for using BFCs as the basic element for EC‐biosensing and especially EC‐logic biosensing applications. The fabrication and design of such self‐powered EC‐biosensing and EC‐logic biosensing are described along and different new approaches for BFCs‐based EC‐biosensing and EC‐logic biosensing involving substrate effects, inhibition effects, blocking effects and gene regulation effects. Latest advances in coupling a self‐powered diagnostic operation with logic‐activated drug release functionality are discussed. We conclude with the implications of the new self‐powered biosensing/logic‐biosensing platforms along with future prospects and challenges.     

Problems with the estimation of stochastic differential equations using structural equations models

The present paper deals with the identification and maximum likelihood estimation of systems of linear stochastic differential equations using panel data. So we only have a sample of discrete observations over time of the relevant variables for each individual. A popular approach in the social sciences advocates the estimation of the “exact discrete model” after a reparameterization with LISREL or similar programs for structural equations models. The “exact discrete model” corresponds to the continuous time model in the sense that observations at equidistant points in time that are generated by the latter system also satisfy the former. In the LISREL approach the reparameterized discrete time model is estimated first without taking into account the nonlinear mapping from the continuous to the discrete time parameters. In a second step, using the inverse mapping, the fundamental system parameters of the continuous time system in which we are interested, are inferred. However, some severe problems arise with this “indirect approach”. First, an identification problem may arise in multiple equation systems, since the matrix exponential function denning some of the new parameters is in general not one‐to‐one, and hence the inverse mapping mentioned above does not exist. Second, usually some sort of approximation of the time paths of the exogenous variables is necessary before the structural parameters of the system can be estimated with discrete data. Two simple approximation methods are discussed. In both approximation methods the resulting new discrete time parameters are connected in a complicated way. So estimating the reparameterized discrete model by OLS without restrictions does not yield maximum likelihood estimates of the desired continuous time parameters as claimed by some authors. Third, a further limitation of estimating the reparameterized model with programs for structural equations models is that even simple restrictions on the original fundamental parameters of the continuous time system cannot be dealt with. This issue is also discussed in some detail. For these reasons the “indirect method” cannot be recommended. In many cases the approach leads to misleading inferences. We strongly advocate the direct estimation of the continuous time parameters. This approach is more involved, because the exact discrete model is nonlinear in the original parameters. A computer program by Hermann Singer that provides appropriate maximum likelihood estimates is described.     

Instance-specific multi-objective parameter tuning based on fuzzy logic

Finding good parameter values for meta-heuristics is known as the parameter setting problem. A new parameter tuning strategy, called IPTS, is proposed that is a novel instance-specific method to take the trade-off between solution quality and computational time into consideration. Two important steps in the method are an a priori statistical analysis to identify the factors that determine heuristic performance in both quality and time for a specific type of problem, and the transformation of these insights into a fuzzy inference system rule base which aims to return parameter values on the Pareto-front with respect to a decision maker’s preference.Applied to the symmetric Travelling Salesman Problem and the meta-heuristic Guided Local Search, the approach is consistently faster than a traditional non-instance-specific parameter tuning strategy without significantly affecting solution quality; optimised for speed, computational times are shown to be on average 20 times faster while producing solutions of similar quality. A number of interesting areas for further research are discussed.     

Interval topology on effect algebras

In this paper, we study the interval topology on effect algebras, and prove that effect algebra operation on Hilbert space effect algebra E(H) is not jointly continuous under the interval topology.     

Note on Deduction Theorems in contraction‐free logics

This paper provides a finer analysis of the well‐known form of the Local Deduction Theorem in contraction‐free logics (understood as Tarski‐style finitary structural consequence relations). An infinite hierarchy of its natural strengthenings is introduced and studied. The main results are the separation of its initial four members and the subsequent collapse of the hierarchy.     

Universal quantum logic gates in decoherence-free subspace with atoms trapped in distant cavities

We propose a scheme for implementation of a universal set of quantum logic gates in decoherence-free subspace with atoms trapped in distant cavities connected by optical fibers.The selective dispersive couplings between the ground states and the first-excited states of the atom-cavity-fiber system produce a state-dependent Stark shift,which can be used to implement nonlocal phase gates between two logic qubits.The single-logic-qubit quantum gates are achieved by the local two-atom collision and the Stark shift of a single atom.During all the logic operations,the logic qubits remain in decoherence-free subspace and thus the operation is immune to collective dephasing.     

Ternary Galois field arithmetic operations with optical nonlinear material (OPNLM) switch

Ternary Galois field (GF3) arithmetic can take an important and significant role in future information processing with multi-valued logic (MVL). An all optical circuit for two arithmetical operations (addition and multiplication) in ternary Galois field with OPNLM switch is proposed and discussed. The different states of polarization of light are taken as different logic states. An outline of Ternary Galois field sum of product (TGFSOP) is also discussed. Mathematical simulation has confirmed the result.     

3D cerebrovascular segmentation combining fuzzy vessel enhancement and level-sets with anisotropic energy weights

The aim of this work is to present and evaluate a level-set segmentation approach with vesselness-dependent anisotropic energy weights, which focuses on the exact segmentation of malformed as well as small vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) datasets.     

Orthogonal addressable monolayers for integrating molecular logic

Plug and play: The mimicking of integrated circuits by using two individual monolayers (molecular chips) is shown. These monolayers can be individually addressed using identical inputs. Upon combination of their optical outputs, the input/output characteristics of a molecular encoder is obtained. Since the encoder functionality is only displayed when both chips are active, the device behaves according to a plug-and-play principle (In=input; see picture).